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Journal of Applied Remote Sensing

Conditioning of reflectance signals by linear diffusion for improving narrow-band ratio-based remote-sensing bottom depth retrieval in shallow coastal waters
Author(s): Anthony M. Filippi; Toshiro Kubota
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Paper Abstract

Ratio-based bottom depth-retrieval algorithms are conceptually simple relative to other algorithms and can be effective. The objective of this study was to determine the utility of imposing a spatial-smoothing assumption on three ratio-based, feed-forward remote-sensing bathymetry algorithms: Polcyn et al., Stumpf et al., and Dierssen et al. We consider three smoothing operators: median, Savitzky-Golay, and linear diffusion with data fidelity, applied in three domains: spatial, spectral, and spectral-spatial. Thus, we consider nine smoothing methods. In addition, we consider two points at which smoothing is applied: one before the inversion process (pre-smoothing) and the other after the inversion process (post-smoothing). Our new formulations were tested with synthetic data, in situ remote-sensing reflectance, and simultaneous acoustic bathymetry, acquired in optically shallow waters. Analysis and results from the synthetic-data experiment indicate that pre-smoothing method is more effective than post-smoothing method. The field-data experiments indicate that spatial-domain smoothing is effective regardless of the type of smoothing operator, whereas spectral smoothing is not. Spectral-spatial-domain smoothing is as effective as spatial-domain smoothing, but is prone to over-segmentation. Effectiveness of spatial pre-smoothing was observed with every ratio-based inversion method, which suggests potential universal applicability of smoothing operators to ratio-based algorithms.

Paper Details

Date Published: 1 August 2009
PDF: 27 pages
J. Appl. Remote Sens. 3(1) 033539 doi: 10.1117/1.3211116
Published in: Journal of Applied Remote Sensing Volume 3, Issue 1
Show Author Affiliations
Anthony M. Filippi, Texas A&M Univ. (United States)
Toshiro Kubota, Susquehanna Univ. (United States)

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